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		   B O S T O N   U N I V E R S I T Y
                                       
		      Computer Science Department
                                       
			  C O L L O Q U I U M
                                       
		       Wednesday March 1, 1995
                                       
				 3:00pm
		       (Coffee served at 2:30pm)
                                       
			 Seminar Room / MCS 135
                                       

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               Self-Describing Files + Smart Modules =
                    Parallel Program Visualization

                       Robert H. Halstead, Jr.
		      DEC Cambridge Research Lab

  Many tools have been built for gathering and visualizing parallel
  program performance data, but all too often these tools are (1) tied
  closely to a specific programming system or computing model and (2)
  monolithic and hard to customize.  We attack problem (1) by using SDF, a
  self-describing file format that allows a flexible representation of
  performance information.  An SDF file can be processed as a sequence of
  named records containing named fields and yet retain the efficiency
  normally associated with custom-designed binary data representations.
  Descriptive annotations can be included to further document the contents
  of an SDF file.

  To attack problem (2), we are implementing a system in which reusable
  performance analysis and visualization modules can be combined in a wide
  range of configurations.  These modules use SDF for their inputs and
  outputs and are "smart" in that they automatically use the annotations
  and mnemonic names present in their input data sets to pick appropriate
  default behaviors, which can be modified interactively if desired.  Key
  to this design is the classification of performance information into
  data types such as "event log" and "histogram," along with the
  definition of suitable conventions for annotating SDF files containing
  information of each type.  Although this project has been motivated by
  the problems of understanding the behavior of parallel programs, it has
  applications to visualizing the execution of sequential as well as
  parallel programs.

Host: Prof. Mark Crovella
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For colloquium info, including directions, see http://cs-www.bu.edu/colloquium
   For more information contact Prof. Mark Crovella <crovella@bu.edu>
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